From 9465f5748c82c87220b2bc66a63e81be0c1843ce Mon Sep 17 00:00:00 2001 From: Dhravya Shah Date: Fri, 16 Jan 2026 12:08:24 -0800 Subject: [PATCH] trying to make gemini live work with pipecat --- packages/pipecat-sdk-python/pyproject.toml | 2 +- .../src/supermemory_pipecat/service.py | 92 +- packages/pipecat-sdk-python/uv.lock | 2190 +++++++++++++++++ 3 files changed, 2282 insertions(+), 2 deletions(-) create mode 100644 packages/pipecat-sdk-python/uv.lock diff --git a/packages/pipecat-sdk-python/pyproject.toml b/packages/pipecat-sdk-python/pyproject.toml index 21ce0cdf..1c25b6a2 100644 --- a/packages/pipecat-sdk-python/pyproject.toml +++ b/packages/pipecat-sdk-python/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "supermemory-pipecat" -version = "0.1.0" +version = "0.1.1" description = "Supermemory integration for Pipecat - memory-enhanced conversational AI pipelines" readme = "README.md" license = "MIT" diff --git a/packages/pipecat-sdk-python/src/supermemory_pipecat/service.py b/packages/pipecat-sdk-python/src/supermemory_pipecat/service.py index ab07e672..b4ac5d87 100644 --- a/packages/pipecat-sdk-python/src/supermemory_pipecat/service.py +++ b/packages/pipecat-sdk-python/src/supermemory_pipecat/service.py @@ -13,7 +13,13 @@ from typing import Any, Dict, List, Literal, Optional from loguru import logger from pydantic import BaseModel, Field -from pipecat.frames.frames import Frame, LLMContextFrame, LLMMessagesFrame +from pipecat.frames.frames import ( + Frame, + LLMContextFrame, + LLMMessagesFrame, + LLMMessagesUpdateFrame, + TranscriptionFrame, +) from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame from pipecat.processors.frame_processor import FrameDirection, FrameProcessor @@ -289,6 +295,85 @@ class SupermemoryPipecatService(FrameProcessor): logger.debug(f"Enhanced context with {total_memories} memories") + async def _handle_transcription(self, frame: TranscriptionFrame) -> None: + """Handle transcription frames from speech-to-speech models like Gemini Live. + + This retrieves relevant memories and injects them via LLMMessagesUpdateFrame, + and stores user transcriptions for future retrieval. + + Args: + frame: The transcription frame containing user speech text. + """ + if not frame.text or not frame.text.strip(): + return + + user_text = frame.text.strip() + + # Skip if same query (avoid duplicate processing) + if self._last_query == user_text: + return + + self._last_query = user_text + logger.debug(f"Processing transcription for memory: {user_text[:100]}...") + + # Retrieve memories and inject them + try: + memories_data = await self._retrieve_memories(user_text) + await self._inject_memories_for_speech_to_speech(memories_data) + except MemoryRetrievalError as e: + logger.warning(f"Memory retrieval failed: {e}") + + # Store the user message in memory + user_message = {"role": "user", "content": user_text} + asyncio.create_task(self._store_messages([user_message])) + + async def _inject_memories_for_speech_to_speech( + self, memories_data: Dict[str, Any] + ) -> None: + """Inject memories for speech-to-speech models via LLMMessagesUpdateFrame. + + Args: + memories_data: Raw memory data from Supermemory API. + """ + profile = memories_data["profile"] + + deduplicated = deduplicate_memories( + static=profile["static"], + dynamic=profile["dynamic"], + search_results=memories_data["search_results"], + ) + + total_memories = ( + len(deduplicated["static"]) + + len(deduplicated["dynamic"]) + + len(deduplicated["search_results"]) + ) + + if total_memories == 0: + logger.debug("No memories found to inject for speech-to-speech") + return + + include_profile = self.params.mode in ("profile", "full") + include_search = self.params.mode in ("query", "full") + + memory_text = format_memories_to_text( + deduplicated, + system_prompt=self.params.system_prompt, + include_static=include_profile, + include_dynamic=include_profile, + include_search=include_search, + ) + + if not memory_text: + return + + # Emit LLMMessagesUpdateFrame with memory context + memory_message = {"role": "user", "content": memory_text} + await self.push_frame( + LLMMessagesUpdateFrame(messages=[memory_message], run_llm=False) + ) + logger.debug(f"Injected {total_memories} memories for speech-to-speech model") + async def process_frame(self, frame: Frame, direction: FrameDirection) -> None: """Process incoming frames, intercept context frames for memory integration. @@ -307,6 +392,11 @@ class SupermemoryPipecatService(FrameProcessor): elif isinstance(frame, LLMMessagesFrame): messages = frame.messages context = LLMContext(messages) + elif isinstance(frame, TranscriptionFrame): + # Handle transcription from speech-to-speech models (e.g., Gemini Live) + await self._handle_transcription(frame) + await self.push_frame(frame, direction) + return if context: try: diff --git 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